Last updated: 2021-06-28
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Knit directory: factor_analysis/
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We used the PLIER R package with the collection of 12999 gene sets as a prior information matrix priorMat available in the package comprising canonical, immune and chemgen pathways from MSigDB (same with the eLife paper)
We used 26 immune and blood cell traits in this part, they are: “mch”,“mchc”,“mcv”,“rdw”,“ret”,“baso”,“plt”,“pct”,“pdw”,“mpv”,“hct”,“hgb”,“ret”,“mono”,“T1D”, “EUR.IBD”,“EUR.UC”,“EUR.CD”,“ukb.allasthma”,“eo”,“wbc”,“rbc”,“myeloid_wbc”,“gran”,“lymph”,“neut”,“allergy”
We got 98 LVs.
We have 2548 trait-factor pairs in total. 31 pairs have more than 2 SNPs with FDR <0.2.
There are 4 pairs show sign consistency (have p-values < 0.05 in resampling, 2.58 fold enrichment). There are 1 pairs at p-value < 0.01, 3.23 fold enrichment).
For the pairs have p-value < 0.05 in resampling, we checked the effect size correlation could be due to reverse causality.
We first used all SNPs associated with traits(pval<5E-8). We computed the MBE estimator and the p-values of the estimator. When computing the IVW, we exchanged the beta.outcome and beta.exposure.
Then we removed the SNPs have FDR < 0.2, just used the remaining SNP to compute IVW and do the fitting.
**The suffix "_reverse" are the results for traits -> LV (using all candidate SNPs after LD Clumping), the suffix "_rremove" are the results for traits -> LV (using all candidate SNPs after LD Clumping but remove the SNPs have fdr < 0.2)**
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sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)
Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] workflowr_1.6.2
loaded via a namespace (and not attached):
[1] Rcpp_1.0.5 rstudioapi_0.11 whisker_0.3-2 knitr_1.30
[5] magrittr_1.5 R6_2.4.1 rlang_0.4.8 highr_0.8
[9] stringr_1.4.0 tools_3.6.1 DT_0.15 xfun_0.18
[13] git2r_0.26.1 crosstalk_1.1.0.1 htmltools_0.5.0 ellipsis_0.3.1
[17] rprojroot_1.3-2 yaml_2.2.1 digest_0.6.25 tibble_3.0.3
[21] lifecycle_0.2.0 crayon_1.3.4 later_1.1.0.1 htmlwidgets_1.5.2
[25] vctrs_0.3.4 promises_1.1.1 fs_1.5.0 glue_1.4.2
[29] evaluate_0.14 rmarkdown_1.13 stringi_1.5.3 compiler_3.6.1
[33] pillar_1.4.6 backports_1.1.10 jsonlite_1.7.1 httpuv_1.5.1
[37] pkgconfig_2.0.3